An Interactive Approach for Project Selection

This paper describes an interactive method for presenting a sequence of feasible sets of indivisible projects to a decision-maker. For each set as a whole, the decision-maker evaluates its utilities with respect to each of several attributes; the utilities are then combined to give a single utility for the set.A sequence of zero-one programmes is used to ensure that the only sets presented are those which are feasible and which are not contained in larger feasible sets. The sets are presented in descending order of size, and the presentation can be terminated by the decision-maker or by supplementary rules.The method for presenting sets can be used in other contexts in which complete enumeration of possible sets would otherwise be required.     

A Note on Multiplicative Utility in Interactive Project Selection

In an earlier paper, the authors presented an interactive method for project selection. The method used additive utilities. This note briefly reports the appropriate modifications for using multiplicative utilities.     

A Discrete Approach to the Prime Number Theorem

An elementary proof of the fundamental theorem on prime numbers is obtained. The result is obtained by defining a new sieve which permits to estimate the number of primes less than an arbitrary N by solving a simple difference equation.     

一种直觉模糊多属性群决策方法及其在群决策中的应用

对以直觉模糊数形式表示的信息和属性权重完全未知的多属性群决策问题进行了研究.提出了一种基于熵值的直觉模糊数距离测度方法,同时对传统的比较得分函数和精确函数的直觉模糊数排序方法进行了改进,定义了一种新的排序公式;进而利用此距离度量公式,引入到基于直觉模糊数之间距离的离差最大化方法中,确定属性的权重,提出了一种基于属性权重完全未知的直觉模糊多属性群决策方法.最后,将此方法运用在ERP选型中.     

Statistical Approach to Modulational Instability in Nonlinear Discrete Systems

We use a statistical approach to investigate the modulational instability (Benjamin-Feir instability) in several nonlinear discrete systems: the discrete nonlinear Schrodinger (NLS) equation, the Ablowitz-Ladik equation, and the discrete deformable NLS equation. We derive a kinetic equation for the two-point correlation function and use a Wigner-Moyal transformation to write it in a mixed space-wave-number representation. We perform a linear stability analysis of the resulting equation and discuss the obtained integral stability condition using several forms of the initial unperturbed spectrum (Lorentzian and δ-spectrum). We compare the results with the continuum limit (the NLS equation) and with previous results.__________Translated from Teoreticheskaya i Matematicheskaya Fizika, Vol. 144, No. 1, pp. 56–63, July, 2005.     

Combined MCDA–IP Approach for Project Selection in the Electricity Market

The European policy target of substantially increasing the share of renewable energy in electricity generation, in combination with national subsidization support schemes, has strongly motivated private investors towards this business sector. In Greece, this interest is particularly apparent in the case of wind energy exploitation, due to a favourable legislative framework and the important wind potential available in several Greek regions. In such endowed regions, a very high number of applications were submitted to the competent authority, most of which compete for the same most attractive (windy) sites. The selection among these applications is a multicriteria problem that has been solved with the support of a Decision-Aid tool combining the multicriteria classification method ELECTRE-TRI with Integer Linear Programming. The developed approach takes into account both, the performances of the applications to the evaluation criteria, as well as a number of technical and policy constraints.     

Fuzzy Pattern Recognition Approach to Construction Contractor Selection

Contractor selection is a complex process crucial to ensuring the success of construction projects. Existing methods by which owners select a suitable contractor have been inadequate because it is difficult for decision-makers to evaluate contractor bids against inexact qualitative criteria. The purpose of this paper is to propose a Multiple-layer Fuzzy Pattern Recognition (MFPR) approach to solve contractor selection problem. Integrating judgments, experience and preferences of decision-makers, this paper uses the paired comparison method to decide relative membership degrees of qualitative criteria as well as weights of the criteria set, a case study for a channel construction project was used to demonstrate the feasibility of this approach. The findings clearly indicate that the techniques may successfully harmonize different opinions and reach a group consensus.     

投资组合模型的分式规划解法

以E-SV风险测度为基础提出了组合证券投资决策的效用函数,并建立了基于分式规划的投资组合选择模型,利用变换,把求解分式规划的问题转化为求解非分式规划问题。     

R&D Project Selection in a Multidimensional Environment: A Practical Approach

This paper investigates the R&D project selection problem within government departments. The Department of National Defence is taken as a case in point. The multidimensional character of the problem is detailed, and existing methods for priority allocation are briefly surveyed. Two basic models for selecting projects are described. One of these, the ordinal intersection method, was found to be the most appropriate for the actual problem settings investigated. An illustrative example is given, and concluding remarks are made.     

一种有交易费用的交互式组合证券投资方法

本基于乘积最大化准则，提出一种新的交互式组合证券投资方法，即将不可微的双目标规划问题转化为可微的单目标规划问题。该方法可以充分考虑投资的要求，在考虑交易费用的前提下，在整个投资方案达到投资要求底限的同时，实现收益和风险的权衡。     

A Confidence Region Approach to Tuning for Variable Selection

We develop an approach to tuning of penalized regression variable selection methods by calculating the sparsest estimator contained in a confidence region of a specified level. Because confidence intervals/regions are generally understood, tuning penalized regression methods in this way is intuitive and more easily understood by scientists and practitioners. More importantly, our work shows that tuning to a fixed confidence level often performs better than tuning via the common methods based on Akaike information criterion (AIC), Bayesian information criterion (BIC), or cross-validation (CV) over a wide range of sample sizes and levels of sparsity. Additionally, we prove that by tuning with a sequence of confidence levels converging to one, asymptotic selection consistency is obtained, and with a simple two-stage procedure, an oracle property is achieved. The confidence-region-based tuning parameter is easily calculated using output from existing penalized regression computer packages. Our work also shows how to map any penalty parameter to a corresponding confidence coefficient. This mapping facilitates comparisons of tuning parameter selection methods such as AIC, BIC, and CV, and reveals that the resulting tuning parameters correspond to confidence levels that are extremely low, and can vary greatly across datasets. Supplemental materials for the article are available online.     

A General Approach to Dyadic Periodic Interpolation Based on Discrete Sigma-Pi Orthogonality

Starting with some well known formulas of discrete sigma-pi orthogonality of bipolar vectors we introduce a quite general and easy strategy to obtain periodic interpolation schemes on dyadic grids including fast algorithms for explicit calculation. As special cases of our presented approach we mention dyadic trigonometric and Walsh-type interpolation.     

Optimal Control for Utility Portfolio Selection with Liability

In this paper we use stochastic optimal control theory to investigate a dynamic portfolio selection problem with liability process, in which the liability process is assumed to be a geometric Brownian motion and completely correlated with stock prices. We apply dynamic programming principle to obtain Hamilton-Jacobi-Bellman (HJB) equations for the value function and systematically study the optimal investment strategies for power utility, exponential utility and logarithm utility. Firstly, the explicit expressions of the optimal portfolios for power utility and exponential utility are obtained by applying variable change technique to solve corresponding HJB equations. Secondly, we apply Legendre transform and dual approach to derive the optimal portfolio for logarithm utility. Finally, numerical examples are given to illustrate the results obtained and analyze the effects of the market parameters on the optimal portfolios.     

A Population-Based Approach to the Resource-Constrained Project Scheduling Problem

We present a population-based approach to the RCPSP. The procedure has two phases. The first phase handles the initial construction of a population of schedules and these are then evolved until high quality solutions are obtained. The evolution of the population is driven by the alternative application of an efficient improving procedure for locally improving the use of resources, and a mechanism for combining schedules that blends scatter search and path relinking characteristics. The objective of the second phase is to explore in depth those vicinities near the high quality schedules. Computational experiments on the standard j120 set, generated using ProGen, show that our algorithm produces higher quality solutions than state-of-the-art heuristics for the RCPSP in an average time of less than five seconds.     

Utility Indifference Pricing: A Time Consistent Approach

Abstract

This article considers the optimal portfolio selection problem in a dynamic multi-period stochastic framework with regime switching. The risk preferences are of exponential (CARA) type with an absolute coefficient of risk aversion that changes with the regime. The market model is incomplete and there are two risky assets: tradable and non-tradable. In this context, the optimal investment strategies are time inconsistent. Consequently, the subgame perfect equilibrium strategies are considered. The utility indifference ask price of a contingent claim written on the risky assets is computed through an indifference valuation algorithm. By running numerical experiments, we examine how this price varies in response to changes in model parameters.